The Information technology for building a seamless multi-temporal mosaic from radar space images
One of the most important factors influencing the planet as a whole and the continent in particular is the processes of destruction of the Antarctic ice sheets. Remote sensing images have become an important means of information acquisition. Visualization of several radar mosaics for different time substantially enhances observation of the ice sheets by showing dynamics of development of cracks, motion of icebergs, directions of streams near the surface of water along the coastline and dynamics of the ice field. This work presents the information technology of building a seamless imagery mosaic coverage of satellite radar scenes. The data under consideration are level-1 ground range detected Sentinel-1 products with dualpolarisation. Since not in all Path/Frame combinations scenes had two polarizations, HH and HV, polarization HH was chosen as the main one. As the direction of imaging, both ascending and descending scenes were chosen. For decreasing the volume of computations, scenes for the mosaic of Antarctica resampled to the spatial resolution of 120 meters and presented in the WGS-84 / Antarctic Polar Stereographic projection. 71% of the created coverage of Antarctica, when scenes are cyclically changed, reflects the changes in time of the coastline of the continent well. The key points related to the technology of preparation of the Sentinel-1 scenes for building the mosaic are presented. The first scene in each pair, save for the first pair, is a mosaic in itself. The method of stitching of the scenes into a mosaic is based on the process of geometric analysis of location of pixels overlapping in the scenes. The main results are shown in a fragment of the mosaic coverage of Antarctica. Experiments show that the technology can achieve automatic panoramic mosaic of the survey area.
Baumhoer Celia A., Dietz Andreas J., C. Kneisel, Kuenzer C. Automated Extraction of Antarctic Glacier and Ice Shelf Fronts from Sentinel-1 Imagery Using Deep Learning, Remote Sens. 2019, 11(21), 2529.
Fürst J.J., Durand G., Gillet-Chaulet F., Tavard L., Rankl M., Braun M., Gagliardini O. The safety band of Antarctic ice shelves, Nat. Clim. Chang. 2016, 6, 479–482.
Copernicus Open Access Hub. Available online:
https://scihub.copernicus.eu/ (accessed on 28 November 2019).
Jezek K.C., Curlander J.C., Carsey F., Wales C., Barry R. G. RAMP AMM-1 SAR Image Mosaic of Antarctica. Version 2. Boulder, Colorado USA. NSIDC: National Snow and Ice Data Center, 2013.
Haran T., Bohlander J., Scambos T., Painter T., Fahnestock M. MODIS Mosaic of Antarctica 2003-2004 (MOA2004) Image Map. Boulder, Colorado USA: National Snow and Ice Data Center, 2005.
Haran T., Bohlander J., Scambos T., Painter T., Fahnestock M. MODIS Mosaic of Antarctica 2008-2009 (MOA2009) Image Map. Boulder, Colorado USA: National Snow and Ice Data Center, 2014.
Yang Y., Gao, Y., Li H., Han Y. An Algorithm for Remote Sensing Image Mosaic Based on Valid Area. In: 2011 International Symposium on Image and Data Fusion (ISIDF 2011). IEEE, Piscataway, 2011.
Lu T., Li S., Fu W. Fusion Based Seamless Mosaic for Remote Sensing Images In.:Sens Imaging,2014,15:101.https://doi.org/10.1007/s11220-014-0101-0.
Luo Yi, Flett Dean. Sentinel-1 data border noise removal and seamless SAR mosaic generation, Proceedings, 2018, 2(7), 330. doi:10.3390/ecrs-2-05143.